class_docstr: A class that tokenizes and otherwise processes text to be encoded
  by a BERT model.
docstr: Generate tokens for given sentence
  
  :param sentence: sentence to be tokenized
  :type sentence: str
  :return: A list of tokens
  :rtype List
docstr_tok: ["Generate","tokens","for","given","sentence",":","param","sentence",":","sentence","to","be","tokenized",":","type","sentence",":","str",":","return",":","A","list","of","tokens",":","rtype","List"]
code: def generate_tokens(self, sentence: str) -> List:
      """Generate tokens for given sentence
  
      :param sentence: sentence to be tokenized
      :type sentence: str
      :return: A list of tokens
      :rtype List
      """
      return self.get_tokenizer().tokenize(sentence)
  
file_path: interpret-text/python/interpret_text/experimental/common/preprocessor/bert_preprocessor.py
imports: import pandas
  from typing import List
  from interpret_text.experimental.common.base_explainer import BaseTextPreprocessor
  from transformers import BertTokenizer
label_desc: Use image node_id 4 for calling the BertPreprocessor obj's underlying member method code with example usage: obj.generate_tokens(sentence) and returns: self